Earn these career-relevant skills in weeks, not years.
- Analyze the role of statistics in psychological research.
- Discriminate between descriptive and inferential statistics.
- Compare the four different levels of measurement.
- Interpret psychological data using descriptive statistics.
- Create graphs and tables with descriptive statistics in Microsoft® Excel®.
- Calculate a z score to understand its purpose.
- Identify how probability is used in everyday life.
- Explain the role of probability in statistical analysis using the standard normal distribution.
- Determine the null and alternative hypotheses.
- Determine the severity of Type I and Type II errors as they relate to hypothesis testing.
- Explain the meaning of statistical significance.
- Determine when a t test and z test are used.
- Explain when the t test for independent groups should be used.
- Interpret data from calculated test statistics.
- Interpret calculated results of an ANOVA.
- Interpret Tukey’s post hoc test.
- Explain the advantages of using an ANOVA over the use of multiple t tests.
- Explain the difference between correlation and causation.
- Interpret statistical significance in reference to the correlation coefficient for meaningfulness.
- Evaluate the Microsoft® Excel® output of a Pearson product-moment correlation.
- Explain the logic of prediction with linear regression.
- Present statistical analyses.
- Conduct a chi-square test in Microsoft® Excel® and interpret results.